Research on Adaptive Scheduling of Single-arm Cluster Tools for Throughput Ratio of Multiple Wafer Types with Concurrent Processing

doi:10.16182/j.issn1004731x.joss.23-1281

Abstract

Abstract:

Concurrent processing makes the wafer fabrication process prone to deadlocks and completion node ambiguity. A Petri net model is established to describe the system operation process by taking for the single-arm cluster tools for fully parallel processing of two wafer types as the research object, and a control strategy is developed to avoid the system deadlock. Based on the Petri net model, the temporal properties of the system is analyzed based on earliest starting strategy, and the action cycle sequence of robot is determined during the monitoring cycle for different scenarios of lot switching in a single production monitoring cycle. An adaptive scheduling algorithm is developed to obtain the production schedule, which can adaptively adjust the ratio of wafer output in each monitoring cycle by setting the type of wafers processed in the shared module, so that the desired production state is continuously approached by adjusting the ratio of wafer output in each monitoring cycle. The feasibility and effectiveness of the algorithm are verified by examples.

Key words: cluster tools, throughput ratio, Petri net, production scheme, adaptive algorithm

CLC Number:

TP273.2

Pan Chunrong, Cui Yu, Xiong Wenqing, Zhou Hao, Luo Jiliang. Research on Adaptive Scheduling of Single-arm Cluster Tools for Throughput Ratio of Multiple Wafer Types with Concurrent Processing[J]. Journal of System Simulation, 2024, 36(12): 2906-2916.

Figures/Tables 9

Fig. 1

Fig. 2

Table 1

Time durations associated with places and transitions

符号	动作说明	时间
x_i,₁	机械手将手中的晶圆装载至C_i 模块中， $i ∈ {a, b, s}$	l(装载时长)
x_0,1	机械手将手中的晶圆装载至真空锁中	l(装载时长)
x_i,₂	机械手从C_i 模块中卸载晶圆至机械手上， $i ∈ {a, b, s}$	u(卸载时长)
x_0,2	机械手从真空锁中卸载晶圆至机械手上	u(卸载时长)
t_i,j	机械手夹持着晶圆从C_i 模块移动到C_j 模块， $i, j ∈ {0, a, b, s}$	m(移动时长)
y_i	机械手空载移动到C_i 模块， $i ∈ {a, b, s}$	m(移动时长)
y₀	机械手空载移动到真空锁	m(移动时长)
p_i	晶圆在C_i 模块中加工， $i ∈ {0, a, b, s}$	τ_i ∈[α_i，∞](晶圆在C_i 模块停留时长)
q_i	机械手在C_i 模块等待卸载晶圆， $i ∈ {a, b, s}$	ω_i ∈[0，∞](在C_i 模块等待时长)
q₀	机械手在真空锁等待卸载晶圆	ω₀∈[0，∞](在真空锁等待时长)
z_i,j	用于连接两个相邻的变迁， $i ∈ N 3, j ∈ {1, 2}$	0(无时间关联)

Table 1

Fig. 3

Fig. 4

Fig. 5

Table 2

Table 3

Fig. 6

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WFP	算法1				算法2
WFP	最佳的SPMAS	最佳晶圆产出比例	晶圆总产能	求解时间/s	最佳的SPMAS	最佳晶圆产出比例	晶圆总产能	求解时间/s
(1，1，1)	A	1.21	161	<1	A、B	0.97	156	<1
(1，1，2)	AB	1.00	172	<1	AB、AB	1.00	172	<1
(1，1，3)	ABB	0.92	188	<1	BBB、AAA	1.02	192	<1
(2，1，1)	A	1.05	174	<1	A、A	1.05	174	<1
(2，1，2)	BB	0.92	188	<1	BB、AB	1.06	192	<1
(2，2，2)	AB	1.13	211	<1	AB、BB	0.97	205	<1
(3，2，1)	B	1.13	211	<1	B、B	1.13	211	<1

WFP	算法1		算法2
WFP	晶圆产出比例	误差率Δ/%	晶圆产出比例	误差率Δ/%
(1，1，1)	0.60	40	0.60	40
(1，1，2)	0.75	25	0.75	25
(1，1，3)	0.90	10	0.90	10
(1，1，4)	1.05	5	1.05	5
(1，1，5)	0.87	13	1.01	1
(1，1，6)	1	0	1	0

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